In a new study published in The Lancet Digital Health, scientists at the USC Mark and Mary Stevens Neuroimaging and Informatics Institute ( Stevens INI ) have discovered that the brains of people who experience severe physical impairment after a stroke may reorganize themselves in unexpected ways, showing signs of "younger" brain structure in undamaged regions as they adapt to injury.
The international research effort is part of the Enhancing NeuroImaging Genetics through Meta-Analysis ( ENIGMA ) Stroke Recovery Working Group, which analyzed brain scans from more than 500 stroke survivors across 34 research sites in eight countries. Using deep learning models trained on tens of thousands of MRI scans, the researchers estimated the "brain age" of different regions in each hemisphere to see how stroke damage affects brain structure and recovery.
"We found that larger strokes accelerate aging in the damaged hemisphere but paradoxically make the opposite side of the brain appear younger," said Hosung Kim, PhD , associate professor of research neurology at the Keck School of Medicine of USC and co-senior author of the study. "This pattern suggests the brain may be reorganizing itself, essentially rejuvenating undamaged networks to compensate for lost function."
The research team used an advanced form of artificial intelligence known as a graph convolutional network to predict the biological age of 18 brain regions from MRI data. The difference between a person's predicted brain age and their actual chronological age, known as the brain-predicted age difference (brain-PAD), served as a sensitive marker of neural health.
When the team associated these measurements with motor performance scores, they found a striking pattern: stroke survivors with severe movement deficits, even after more than 6 months of rehabilitation, showed younger-than-expected brain age in regions opposite the lesion, particularly within the frontoparietal network, a key system involved in motor planning, attention, and coordination.
"These findings suggest that when stroke damage leads to greater movement loss, undamaged regions on the opposite side of the brain may adapt to help compensate," Kim explained. "We saw this in the contralesional frontoparietal network, which showed a more 'youthful' pattern and is known to support motor planning, attention, and coordination. Rather than indicating full recovery of movement, this pattern may reflect the brain's attempt to adjust when the damaged motor system can no longer function normally. This gives us a new way to see neuroplasticity that traditional imaging could not capture."
The study was conducted through ENIGMA, a global alliance that unites data from more than 50 countries to better understand the brain across diseases. Researchers harmonized MRI data and clinical measures across dozens of cohorts to build the world's largest stroke neuroimaging dataset of its kind.
"By pooling data from hundreds of stroke survivors worldwide and applying cutting-edge AI, we can detect subtle patterns of brain reorganization that would be invisible in smaller studies. These findings of regionally differential brain aging in chronic stroke could eventually guide personalized rehabilitation strategies," said Arthur W. Toga, PhD , director of the Stevens INI and Provost Professor at USC.
The team plans to expand their work to include longitudinal studies tracking patients from the acute to chronic stages of stroke recovery. By observing how patterns of brain aging and reorganization develop over time, clinicians might be able to customize interventions based on each patient's unique neural adaptation process, ultimately improving recovery outcomes and quality of life in the near future.
Learn more about associations between contralesional neuroplasticity and motor impairment by viewing this video made by the Stevens INI .
About the study
The study, "Deep learning prediction of MRI-based regional brain age reveals contralesional neuroplasticity associated with severe motor impairment in chronic stroke: A worldwide ENIGMA study," was funded by the National Institutes of Health (NIH) grant R01 NS115845 and supported by international collaborators from institutions including the University of British Columbia, Monash University, Emory University, and the University of Oslo.
